معرفی
Arto Klami serves as an Associate Professor in the Department of Computer Science at the University of Helsinki's Faculty of Science, where he also leads the Diversity in Society and Life (DIVSOL) doctoral program. His research spans machine learning, artificial intelligence, and statistics with applications across multiple domains including food science, astronomy, and industrial engineering. Klami maintains active collaborations with Helsinki Institute for Information Technology and leads multiple research projects funded by the Academy of Finland and Business Finland.
Professor Klami's research focuses on probabilistic modeling, Bayesian methods, and geometric approaches to machine learning. His work bridges theoretical foundations with practical applications, particularly in developing methods for small data scenarios, prior knowledge integration, and geometric deep learning. His recent publications demonstrate expertise in normalizing flows, manifold learning, and Riemannian geometry applied to statistical problems, alongside domain-specific applications in food science, astronomy, and industrial monitoring systems.
Klami's publication record shows a strong trajectory with 97 research outputs through 2025, including numerous high-impact articles in leading journals and conferences. His work spans both theoretical machine learning advancements and applied research in diverse fields such as food preservation, asteroid surface analysis, and industrial fouling detection. A notable trend is his increasing focus on cross-disciplinary applications of probabilistic AI methods, particularly in addressing real-world challenges with limited data.
Scientific recognition includes:
- Best paper award at the 15th Koli Calling conference on computing education research (2015)
- Best paper award in Asian Conference on Machine Learning (2012)
- Senior good researcher award from the Department of Computer Science (2014)
As an academic leader, Klami has supervised 9 doctoral theses and contributed to 33 academic activities including peer review for top journals like the Journal of the American Statistical Association. He leads five major research projects through 2030, with significant funding from the Academy of Finland, including FoodID (NSF Global Centers), DIVSOL profiling initiative, and projects on flexible priors and virtual laboratories. His work with the Nordic Probabilistic AI School demonstrates commitment to community building in machine learning.
Klami directs research teams working on probabilistic AI applications, with particular emphasis on the Virtual Laboratories project and Sustainable Industrial Ultrasonic Cleaning initiative. His Helsinki-based research group maintains strong industry connections through partnerships with Orion Oyj and Silo AI Oy, translating academic research into practical industrial solutions.
